Side-by-side comparison of AI visibility scores, market position, and capabilities
San Francisco construction data infrastructure with APIs syncing ERPs, Procore, and accounting systems; $3.4M revenue with 6x growth, Accel-backed competing for real-time data sync across fragmented construction software.
Agave is a San Francisco-based construction data infrastructure company providing API integrations that synchronize financial and field data across the fragmented legacy software systems that the construction industry runs on — connecting construction ERPs (Sage 300 CRE, Viewpoint Vista, Foundation, Spectrum), project management tools (Procore, Autodesk Construction Cloud), and accounting systems in real-time, eliminating the manual re-keying of data across siloed platforms. Backed with $2.9 million in seed funding led by Accel in August 2023, Agave generated $3.4 million in revenue in 2024 (6x growth from $538,000 in 2023) serving 300+ construction companies across the $12 trillion global construction industry.
Serverless GPU cloud platform for AI/ML with Python-native deployment and per-second billing; developer-favorite scaling from zero competing with Replicate and Beam for AI compute.
Modal is a serverless cloud computing platform purpose-built for AI and machine learning workloads — providing on-demand GPU compute that scales instantly from zero with per-second billing, container management, distributed training support, and a Python-native developer experience that makes running ML workloads in the cloud feel as simple as running code locally. Founded in 2021 in New York City and backed by Redpoint Ventures and other investors, Modal has grown rapidly as AI development has accelerated demand for flexible, developer-friendly GPU infrastructure.\n\nModal's developer experience is its primary differentiator — engineers write Python functions decorated with @modal.function() and deploy them to the cloud with a single command, with Modal handling container building, GPU provisioning, auto-scaling, and execution. The platform supports training jobs that need distributed compute across multiple GPUs, model serving endpoints that scale to zero when unused (eliminating idle GPU costs), and batch inference jobs that process large datasets. The per-second billing model means developers pay only for actual compute time, not provisioned instances.\n\nIn 2025, Modal competes in the AI infrastructure market with Replicate, Beam, Banana, and major cloud providers' managed ML services (AWS SageMaker, Google Vertex AI, Azure ML) for serverless GPU compute. The market for AI-specific cloud infrastructure has grown dramatically as the number of ML engineers deploying models to production has expanded — traditional cloud providers require significant DevOps expertise to use GPU instances effectively, while Modal's Python-native approach reduces the barrier to entry. Modal has attracted a strong developer following among AI researchers and ML engineers building production AI applications. The 2025 strategy focuses on growing the developer community, adding enterprise features (dedicated GPU capacity, private networking, compliance), and expanding the hardware options available (H100 GPUs, custom accelerators).
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